The proposed research is aimed at expanding our knowledge of how people compensate for their cognitive limitations, particularly as they age. Many actions are best understood as compensatory, they are undertaken because they reduce the memory and computational demands agents must cope with if they are to seed at their tasks. Our current research on college age students suggests that such compensations occur even in environments, such as computer arcade games, where quick response is required. We hypothesize that: (1) careful empirical and theoretical study will reveal that older people also perform compensatory actions in fast paced environments to reduce internal cognitive demands; (2) compensations spontaneously develop, although they may also be taught; (3) the differential value of compensations teaches us about the relation between computational strategies and cognitive architectures. To test our hypotheses we shall run experiments and construct computer models to simulate the consequences of lesioning key capacities. The primary experimental task is Tetris, a fast paced computer game that involves making quick decisions about rotating and translating simple shapes related to shapes described in the literature on mental rotation. We have constructed a special computational environment for automatically collecting Tetris data at millisecond levels and for creating arbitrary Tetris stimuli. Experiment I examines if the tendency to rotate video shapes in the world, rather than rotate images of them in the head -- a valuable compensatory strategy -- is a tendency that crosses age and motor performance. Experiment II examines if older subjects learn more slowly than young subjects and if their learning rate is sensitive to the initial pace of the game. Additional study of age-related performance will reveal if there are statistically significant differences in the style of play, such as, the average time to first touch the keys, average number of extra rotations, average drop height, percentage of zoids dropped, and so on. Experiment III tests if real time compensating strategies can be learned from explicit instruction. Experiment IV explores via simulations the question whether certain cognitive architectures are more robust to the cognitive deficits typical of aging. We study how the selective control of resources differentially effects performance in each of the models we shall build. In Experiment V we use experiment and theoretical analysis to discover if there are domain specific categories and concepts that human experts operate with in playing Tetris. In Experiment VI we confirm the general idea that interactive, compensatory strategies, outside the Tetris domain, can help agents improve performance, by observing if subjects can recognize letters from randomly oriented parts of those letters faster if they are allowed to rotate those parts. The relevance to health and the aging is that the more we understand how deficits can be compensated for the better we can design user friendly environments and devices for the aged; calibrate the workplace to keep pace with declining capacities, and teach the aged and cognitively limited to compensate for their deficits.